Chris Eliasmith has spent years trying to figure out the ingredients and precise recipe for building a brain. He even has a book coming out in February--called “How to Build A Brain”--describing gray matter, dendritic connections and other brainy anatomy. As he was writing it, it occurred to him that he might want to demonstrate it. So he built Spaun, the most complex simulation of a functioning brain built to date.Spaun, which stands for Semantic Pointer Architecture Unified Network, is a computer model that can recognize numbers, remember them, figure out numeric sequences, and even write them down with a robotic arm. It’s a major leap in brain simulation, because it’s the first model that can actually emulate behaviors while also modeling the physiology that underlies them.The program consists of 2.5 million simulated neurons organized into subsystems that are designed to resemble specific brain regions, including the prefrontal cortex, basil ganglia and thalamus. It has a virtual eye and a robotic arm, and can perform a series of tasks, each different from one another.

What does it take to succeed? What are the secrets of the most successful people? Judging by the popularity of magazines such as Success, Forbes, Inc., and Entrepreneur, there is no shortage of interest in these questions. There is a deep underlying assumption, however, that we can learn from them because it's their personal characteristics--such as talent, skill, mental toughness, hard work, tenacity, optimism, growth mindset, and emotional intelligence-- that got them where they are today. This assumption doesn't only underlie success magazines, but also how we distribute resources in society, from work opportunities to fame to government grants to public policy decisions. We tend to give out resources to those who have a past history of success, and tend to ignore those who have been unsuccessful, assuming that the most successful are also the most competent.But is this assumption correct? I have spent my entire career studying the psychological characteristics that predict achievement and creativity. While I have found that a certain number of traits-- including passion, perseverance, imagination, intellectual curiosity, and openness to experience-- do significantly explain differences in success, I am often intrigued by just how much of the variance is often left unexplained.

Would universal basic income cause people to leave the workforce? New research suggests it would not.

Such proposals, including one that Hillary Clinton considered during her 2016 presidential campaign, include direct payments that ensure each resident has a baseline of income to provide for basic needs. While previous research has focused on the effects of these unconditional cash transfers at the micro level—for example, winning the lottery—this study examined their large-scale impact by looking a government program that has supported Alaska residents for the past 25 years.

In a working paper, associate professor Damon Jones of the University of Chicago Harris School of Public Policy and assistant professor Ioana Marinescu of the University of Pennsylvania School of Social Policy and Practice (formerly of the University of Chicago) examined the effect of unconditional cash transfers on labor markets using the Alaska Permanent Fund Dividend—a payout from a diversified portfolio of invested oil reserve royalties, established in 1982.

They concluded unconditional cash transfers had no significant effect on employment, yet it increased part-time work.

“It is reasonable to expect an unconditional cash transfer, such as a universal income, to decrease employment,” Jones says. “A key concern with a universal basic income is that it could discourage people from working, but our research shows that the possible reductions in employment seem to be offset by increases in spending that in turn increase the demand for more workers.”

With only a few exceptions, every Alaskan who has been a resident for at least 12 months is entitled to a dividend from the Alaska Permanent Fund, which as of August 2017 is worth nearly $61 billion. In recent years, the payment, which residents receive through direct deposit, has averaged about $2,000 a year in a lump sum. But because it is a per-person amount, a household of four could receive more than $8,000.

Jones and Marinescu examined the effects of a large number of people receiving a cash transfer. Notably the researchers found that:

There is no significant effect, positive or negative, on employment as a whole, although part-time work does increase by 1.8 percentage points, or about 17 percent. There is a difference in the effect of the unconditional cash transfer in sectors that produce goods or services that can be traded outside of Alaska and those that cannot. Part-time work increases and employment decreases in the tradable sector, but the effects in the non-tradable sector are insignificant. Any negative effects in the non-tradable sector, meanwhile, are offset by positive macro effects.

Scientists have used a device that fits in the palm of the hand to sequence the human genome.

They say the feat, detailed in the journal Nature Biotechnology, opens up exciting possibilities for using genetics in routine medicine.

It is a far cry from the effort to sequence the first human genome which started in 1990.

The Human Genome Project took 13 years, laboratories around the world and hundreds of millions of dollars.

Since then there has been a revolution in cracking the code of life.

Science enters $1,000 genome era

Prof Nicholas Loman, one of the researchers and from the University of Birmingham, UK, told the BBC: "We've gone from a situation where you can only do genome sequencing for a huge amount of money in well equipped labs to one where we can have genome sequencing literally in your pocket just like a mobile phone.

"That gives us a really exciting opportunity to start having genome sequencing as a routine tool, perhaps something people can do in their own home."

Sequencing technology has the potential to change the way we do medicine.

Analysing the mutated DNA of cancers could be used to pick the best treatment. Or inspecting the genetic code of bacteria could spot antibiotic resistance early.

Prof Loman used the handheld device to track the spread of Ebola during the outbreak in West Africa. Image copyright Oxford Nanopore

static website design is less demanding than others. Moving the envelope documents enable you to move static pages starting with one server then onto the next or starting with one registry then onto the next.

It was the hardest thing I’d ever had to say to my husband, Marc. Three years ago, I sat down and told him: “The idea of having sex just with you for the next 40 years – I can’t do it any more.” But I had come to realise that my life was built around something I didn’t believe in: monogamy.

We had been together for 12 years and had two children, now nine and seven. I love being a mother and I set the bar high from the start – cloth nappies and cooking from scratch. But I needed something more in my emotional and sexual life.

Marc’s reaction was remarkable; he agreed to support me and open our marriage to other partners, although it wasn’t really what he wanted. We started counselling to try to identify the best of what we had, to save it and protect it. Sex is a big part of a relationship, but it is only a part. We didn’t want it to scupper us.

If that sounds difficult, it was. I don’t think we could have done it if we hadn’t spent most of our marriage reading, talking and exploring together.

I quickly embraced the dating scene and discovered another side of my sexual self. I enrolled on lots of sites, where you are asked specific questions about yourself and your preferences. It was illuminating: do I like this? Yes. Do I like that? Well, let’s see. They were the kind of questions I’d never been asked before – and had never asked myself.

I became convinced that traditional relationships are like an air lock. You meet someone. It’s amazing and it’s rare, and then you lock it; you shut the windows and doors, and you try desperately to keep it all to yourselves. Then the air turns sour because there’s no oxygen. You might make a sexual mistake on the spur of the moment because you are craving some – any – contact. Why not live in a world where you can have room for that connection, that spark?

I think most people’s reaction was that Marc should have kicked me out. My immediate family have been supportive, although my mother is still ambivalent. We discuss everything openly, and she understands where I’m coming from, but worries that I’m going to end up on my own. If I do, though, it will be because I have chosen that.

People who choose to be polyamorous often do so after delving deep into themselves and their desires, so it runs close to the kink scene, which was also something I wanted to explore. There’s a temptation to think that, had Marc and I explored these things together, our marriage might have worked without opening it up. I’m not sure that it would have, though, given that he wasn’t into it. It can seem quite intimidating, but I was so ready for it. The first time I went to a fetish club, I felt like I was at home – that I’d found my people.

he most powerful approach in AI, deep learning, is gaining a new capability: a sense of uncertainty.

Researchers at Uber and Google are working on modifications to the two most popular deep-learning frameworks that will enable them to handle probability. This will provide a way for the smartest AI programs to measure their confidence in a prediction or a decision—essentially, to know when they should doubt themselves.

Deep learning, which involves feeding example data to a large and powerful neural network, has been an enormous success over the past few years, enabling machines to recognize objects in images or transcribe speech almost perfectly. But it requires lots of training data and computing power, and it can be surprisingly brittle.

Somewhat counterintuitively, this self-doubt offers one fix. The new approach could be useful in critical scenarios involving self-driving cars and other autonomous machines.

“You would like a system that gives you a measure of how certain it is,” says Dustin Tran, who is working on this problem at Google. “If a self-driving car doesn’t know its level of uncertainty, it can make a fatal error, and that can be catastrophic.”

Language learning will be vital for the future of the UK economy in a post Brexit world. This is in part why employers are desperately looking for graduates with language skills – and, more importantly, intercultural awareness and empathy.

According to a CBI Pearson Education Survey 58% of employers are dissatisfied with school leavers’ language skills. The survey also found that 55% of employers would like to see improvements in students’ intercultural awareness.

Similarly, the British Chamber of Commerce’s 2013 Survey of International Trade states that a large majority of non-exporters cite language and cultural factors as barriers to success.

It may sound like good news then that Google has just released an AI-powered translation earbud, with claims it will instantly translate between 40 different languages using a Pixel smartphone.

A wireless connection to the ear buds allows the user to translate to and from different languages in real time. In the live demo Google showed how the ear bud can translate short phrases –one of the major benefits is said to be: “now you can order your meals like a pro”. In Google’s imagination their software increases intercultural communication and gets rid of language barriers. So will this spell the end of language learning as we know it? Probably not.

​Ergothioneine and glutathione. Hardly household names when it comes to health, but some scientists believe these antioxidants can play a vital role in fighting aging and its associated diseases, and a new study has found mushrooms to be packed with them

Ergothioneine and glutathione. Hardly household names when it comes to health, but some scientists believe these antioxidants can play a vital role in fighting aging and its associated diseases. A new study has found mushrooms to be packed with these compounds, and in good news for fans of funghi-finished pizzas, high temperatures don't seem to alter their effects. One school of thought when it comes to aging is known as the free radical theory. Free radicals are oxygen atoms with unpaired electrons that arise as a by-product of the process in which the body converts food into energy. These highly reactive atoms then travel around the body in search of other electrons to pair up with, causing oxidative damage to the cells, proteins and even DNA in their path. "The body has mechanisms to control most of them, including ergothioneine and glutathione, but eventually enough accrue to cause damage, which has been associated with many of the diseases of aging, like cancer, coronary heart disease and Alzheimer's," said Robert Beelman, professor emeritus of food science and director of the Penn State Center for Plant and Mushroom Products for Health..

A section of a Neuropixels probe (credit: Howard Hughes Medical Institute) In a $5.5 million international collaboration, researchers and engineers have

In a $5.5 million international collaboration, researchers and engineers have developed powerful new “Neuropixels” brain probes that can simultaneously monitor the neural activity of hundreds of neurons at several layers of a rodent’s brain for the first time. Described in a paper published today (November 8, 2017) in Nature, Neuropixels probes represent a significant advance in neuroscience measurement technology, and will allow for the most precise understanding yet of how large networks of nerve cells coordinate to give rise to behavior and cognition, according to the researchers.

Aliens could be everywhere. There are at least 100 billion planets in our galaxy alone, and at least 20% of them could be habitable. Even if a tiny fraction of those planets – less than one percent of one percent – evolved life, there would still be tens of thousands of planets with aliens in our vicinity. But if we want to figure out where to start looking for these neighbours, we need to understand what they might be like and where they might thrive. Ultimately, we want to understand as much as possible about an extraterrestrial species before we encounter it. And yet, making predictions about aliens is hard. The reason is simple: we have only one example – life on Earth – to extrapolate from. Just because eyes and limbs have evolved many times on Earth doesn’t mean they’ll appear even once elsewhere. Just because we are made of carbon and coded by DNA doesn’t mean aliens will be – they could be silicon based and coded by “XNA”. However, as my colleagues and I argue in our new study, published in the International Journal of Astrobiology, there is another approach to making predictions about aliens that gets around this problem. That is to use evolutionary theory as a guiding principle. The theory of natural selection allows us to make predictions that don’t depend on the details of Earth, and so will hold even for eyeless, nitrogen-breathing aliens. Darwin formulated his theory of natural selection long before we knew what DNA was, how mutations appeared, or even how traits were passed on. It is remarkably simple, and requires just a few ingredients to work: variation (some giraffes have longer necks than others), heritability of that variation (long-necked giraffes have long-necked babies) and differential success linked to the variation (long-necked giraffes eat more leaves and have more babies).

Some people can see at a finer resolution than the spacing between individual photo-receptors in the eye – and it's all down to their brains.

Wouldn’t it be great to be able to hear what people whispered behind your back? Or to read the bus timetable from across the street? We all differ dramatically in our perceptual abilities – for all our senses. But do we have to accept what we’ve got when it comes to sensory perception? Or can we actually do something to improve it? Differences in perceptual ability are most obvious for the more valued senses – hearing and vision. But some people have enhanced abilities for the other senses too. For example, there are “supertasters” among us mere mortals who perceive stronger tastes from various sweet and bitter substances (a trait linked with a greater number of taste receptors on the tip of the tongue). It’s not all good news for the supertasters though – they also perceive more burn from oral irritants like alcohol and chilli. Women have been shown to be better at feeling touch than men. Interestingly, this turns out not to really be a gender thing at all, but rather down to having smaller fingers. This means touch receptors that are more closely packed together, and therefore the possibility for perception at a finer resolution. Thus, if a man and woman have the same sized fingers, they will have equivalent touch perception.

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Most religions are populated by an impressive cadre of ghosts, gods, spirits and angels.

If you’ve ever seen a ghost, you have something in common with 18 percent of Americans. But while there’s evidence that our brains are hardwired to see ghosts, the apparitions we see tend to vary. Historians who study and catalogue ghostly encounters across time will tell you that ghosts come in a range of shapes and forms. Some haunt individuals, appearing in dreams or popping up at unexpected times. Others haunt a specific location and are prepared to spook any passersby. Some are the spitting images of what were once real humans. And then there are the noisy and troublesome poltergeists, which appear as uncontrollable supernatural forces instead of people. What might explain such discrepancies? And are some people more likely to see ghosts than others? It turns out that our religious background could play a role. Religion might ease one fear Some argue that religion evolved as a terror management device, a handy way to remove the uncertainty surrounding one of the scariest things we can imagine: death. Almost every religion offers an explanation for what happens to us after we die, with the assurance that death isn’t the end. And there is, in fact, evidence that very religious people don’t fear death as much as others. Protestants, Catholics and Muslims all believe in a day of resurrection and judgment, in which our souls are directed to heaven (“Jannah” in the case of Muslims) or hell based upon our good deeds (or misdeeds) during our time spent on Earth. Catholics also believe in a halfway house called purgatory, in which people who aren’t quite worthy of heaven but are too good for hell can pay their dues before getting a ticket to paradise.

Unable to stay focused? Frequently going away with the fairies? It may be because you have so much brain capacity that it needs to find ways to keep itself occupied, according to new research. A team of psychologists has found a positive correlation between a person's tendency to daydream and their levels of intelligence and creativity. "People tend to think of mind wandering as something that is bad. You try to pay attention and you can't," said one of the team, Eric Schumacher from Georgia Institute of Technology. "Our data are consistent with the idea that this isn't always true. Some people have more efficient brains." The researchers examined the brain patterns of 112 study participants as they lay in an fMRI machine not doing anything in particular and just staring at a fixed point for five minutes. This is known as a resting state scan, and the team used this data to figure out which parts of the participants' brains worked together in unison in what's called the default mode network. These participants also completed a questionnaire about daydreaming, and, once the researchers figured out how their brains worked, tests of executive function, fluid intelligence and creativity. There were several correlations. Those participants who self-reported higher rates of daydreaming had a higher rate of default mode network connectivity in the brain, as well as a higher rate of control between the default mode network and the frontoparietal control network of the brain. Those participants also performed better on the fluid intelligence and creativity tests than the participants who weren't daydreamers.

Over the decades, combinations of various programming techniques have enabled slow spotty progress in AI — punctuated by occasional breakthroughs such as certain expert, decision and planning systems, and mastering Chess and Jeopardy! These approaches, and in particular those focused on symbolic representations, are generally referred to as GOFAI (Good Old-Fashioned AI). Importantly, a key characteristic that they share is that applications are hand-crafted and custom engineered: Programmers figure out how to solve a particular problem, then turning their insights into code. This essentially represents the ‘First Wave’.

In a sign that lab-grown meat is getting closer to finally reaching the market and significantly disrupting traditional meat-producing industries, the US Cattlemen's Association (USCA) is petitioning the United States Department of Agriculture (USDA) to restrict the definition of "beef" and "meat" exclusively to products born, raised and slaughtered in a traditional manner. The petition raises the question: Can lab-grown meat still be called meat?

Lab-grown meat has rapidly moved closer and closer to our market shelves over recent years. Promising tech start-ups such as Memphis Meats are effectively growing edible meat in laboratory conditions from animal cells. Despite refining the process to impressively resemble the look and taste of traditional meat, the technique has been infamously time-consuming and prohibitively expensive, keeping it from being easily scaled up to industrial levels.

Memphis Meats suggests its products will reach the general public by 2021, but another startup called Just (formerly Hampton Creek) is ambitiously planning its first lab-grown meat product to hit the market by the end of 2018. Unsurprisingly, traditional meat producers are viewing the looming disruption as a major threat, and are now officially drawing a line in the sand.

Over the past year, it's become pretty clear that machines can now beat us in many straightforward zero-sum games. A new study from an international team of computer scientists set out to develop a new type of game-playing algorithm – one that can play games that rely on traits like cooperation and compromise – and the researchers have found that machines can already deploy those characteristics better than humans.

Chess, Go and Poker are all adversarial games where two or more players are in conflict with each other. Games such as these offer clear milestones to gauge the progress of AI development, allowing humans to be pitted against computers with a tangible winner. But many real-world scenarios that AI will ultimately operate in require more complex, cooperative long term relationships between humans and machines.

"The end goal is that we understand the mathematics behind cooperation with people and what attributes artificial intelligence needs to develop social skills," says lead author on the new study Jacob Crandall. "AI needs to be able to respond to us and articulate what it's doing. It has to be able to interact with other people."

As time progresses, it seems as if machines ans humans are constantly competing, and according to this article, Artificial Intelligence is gaining on people. This article goes into detail about how a program called “S#” has the ability to cooperate in social interactions better than a human does. The program was tested throughout a series of human-human, machine-machine, and human-machine interactions via video games. The results showed that the interactions that consisted of machine-machine interactions were most sucessful, while the human-machine interactions placed second, and the human-human interactions scored lowest in cooperation. Jacob Crindalls, lead author of the study stated that the goal of the study is “that we understand the mathematics behind cooperation with people and what attributes artificial intelligence needs to develop social skills.” This article is interesting to see especially during a time like today where technology is constantly making advances, and it raises questions as to whether technology may fully surpass human intelligence altogether.

RAVEN: The source’s reputation comes from a university study conducted by Brigham Young University. The ability to observe rests in the experimenter’s perspectives, as well as the expertise which comes from those behind the studies such as Jacob Crindalls, who is the lead author of the study.

Nothing comes for free, especially online. Websites and apps that don’t charge you for their services are often collecting your data or bombarding you with advertising. Now some sites have found a new way to make money from you: using your computer to generate virtual currencies.

Several video streaming sites and the popular file sharing network The Pirate Bay have allegedly been “cryptojacking” their users’ computers in this way, as has the free wifi provider in a Starbucks cafe in Argentina. Users may object to this, especially if it slows down their computers. But given how hard it is for most companies to make money from online advertising, it might be something we have to get used to – unless we want to start paying more for things.

Units of cryptocurrencies such as bitcoin aren’t created by a central bank like regular money but are generated or “mined” by computers solving complex equations. Cryptojacking involves using someone’s computer without their knowledge, perhaps for just seconds at a time, to mine a cryptocurrency.

In the case of bitcoin, mining requires specialised hardware and consumes masses of energy. For example, each bitcoin transaction takes enough energy to boil around 36,000 kettles filled with water. In a year, the whole bitcoin mining network consumes more energy than Ireland.

But bitcoin is not the only show in town and there are many competing cryptocurrences. One of the most successful is Monero, which builds a degree of privacy into transactions (something bitcoin doesn’t do). Currently it requires no specialised hardware for mining, so anyone with computing power to spare can mine it.

Mining usually takes the form of a competition. Whichever computer solves the equation the fastest is rewarded with the money. With Moreno and other similar cryptocurrencies, a pool of computers can work together and share the reward if they win the competition. This allows individual computers to work on a just small part of the mining task. The larger the pool, the more chance there is of winning the reward.

In the Hitchhiker’s Guide to The Galaxy, Douglas Adams’s seminal 1978 BBC broadcast (then book, feature film and now cultural icon), one of the many technology predictions was the Babel Fish. This tiny yellow life-form, inserted into the human ear and fed by brain energy, was able to translate to and from any language.

Web giant Google have now seemingly developed their own version of the Babel Fish, called Pixel Buds. These wireless earbuds make use of Google Assistant, a smart application which can speak to, understand and assist the wearer. One of the headline abilities is support for Google Translate which is said to be able to translate up to 40 different languages. Impressive technology for under US$200.

So how does it work?

Real-time speech translation consists of a chain of several distinct technologies – each of which have experienced rapid degrees of improvement over recent years. The chain, from input to output, goes like this:

Input conditioning: the earbuds pick up background noise and interference, effectively recording a mixture of the users’ voice and other sounds. “Denoising” removes background sounds while a voice activity detector (VAD) is used to turn the system on only when the correct person is speaking (and not someone standing behind you in a queue saying “OK Google” very loudly). Touch control is used to improve the VAD accuracy.

Language identification (LID): this system uses machine learning to identify what language is being spoken within a couple of seconds. This is important because everything that follows is language specific. For language identification, phonetic characteristics alone are insufficient to distinguish languages (languages pairs like Ukrainian and Russian, Urdu and Hindi are virtually identical in their units of sound, or “phonemes”), so completely new acoustic representations had to be developed.

Automatic speech recognition (ASR): ASR uses an acoustic model to convert the recorded speech into a string of phonemes and then language modelling is used to convert the phonetic information into words. By using the rules of spoken grammar, context, probability and a pronunciation dictionary, ASR systems fill in gaps of missing information and correct mistakenly recognised phonemes to infer a textual representation of what the speaker said.

Will you be among the first to pick your kids’ IQ? As machine learning unlocks predictions from DNA databases, scientists say parents could have choices never before possible.

Nathan Treff was diagnosed with type 1 diabetes at 24. It’s a disease that runs in families, but it has complex causes. More than one gene is involved. And the environment plays a role too. So you don’t know who will get it. Treff’s grandfather had it, and lost a leg. But Treff’s three young kids are fine, so far. He’s crossing his fingers they won’t develop it later. Now Treff, an in vitro fertilization specialist, is working on a radical way to change the odds. Using a combination of computer models and DNA tests, the startup company he’s working with, Genomic Prediction, thinks it has a way of predicting which IVF embryos in a laboratory dish would be most likely to develop type 1 diabetes or other complex diseases. Armed with such statistical scorecards, doctors and parents could huddle and choose to avoid embryos with failing grades. IVF clinics already test the DNA of embryos to spot rare diseases, like cystic fibrosis, caused by defects in a single gene. But these “preimplantation” tests are poised for a dramatic leap forward as it becomes possible to peer more deeply at an embryo’s genome and create broad statistical forecasts about the person it would become. The advance is occurring, say scientists, thanks to a growing flood of genetic data collected from large population studies. As statistical models known as predictors gobble up DNA and health information about hundreds of thousands of people, they’re getting more accurate at spotting the genetic patterns that foreshadow disease risk. But they have a controversial side, since the same techniques can be used to project the eventual height, weight, skin tone, and even intelligence of an IVF embryo.

Carbon might be the backbone of organic chemistry, but life on Earth wouldn't be what it is today if it weren't for another critical member of the periodic table – phosphorus.

Transforming run of the mill hydrocarbons into the kinds of molecules that include this important element is a giant evolutionary leap, chemically speaking. But now scientists think they know how such a vital step was accomplished.

Researchers from The Scripps Research Institute in California have identified a molecule capable of performing phosphorylation in water, making it a solid candidate for what has until now been a missing link in the chain from lifeless soup to evolving cells.

In the classic chicken and egg conundrum of biology's origins, debate continues to rage over which process kicked off others in order to get to life. Was RNA was followed by protein structures? Did metabolism spark the whole shebang? And what about the lipids?

No matter what school of abiogenesis you hail from, the production of these various classes of organic molecules requires a process called phosphorylation – getting a group of three oxygens and a phosphorus to attach to other molecules.

Nobody has provided strong evidence in support of any particular agent that might have been responsible for making this happen to prebiotic compounds. Until now.

"We suggest a phosphorylation chemistry that could have given rise, all in the same place, to oligonucleotides, oligopeptides, and the cell-like structures to enclose them," says researcher Ramanarayanan Krishnamurthy.

It's hard coming up with clever new Halloween costume ideas, so why do all the work yourself? Research scientist Janelle Shane decided to enlist her computer to help with the annual task, and she's built a first-of-its-kind neural network that can spit out brand-new Halloween costume ideas. First, she fed her computer data on 4,500 Halloween costume names she crowdsourced from the internet. Then, it was up to the machine to figure out how to riff on those names and toss around new Halloween costume ideas. It did pop out some gibberish, especially at first. But it also came up with ideas like the goddess butterfly, sad pumpkin king, party scarecrow, pickle witch, and this dragon of liberty:

Veteran Kagglers say the opportunities that flow from a good ranking are generally more bankable than the prizes. Participants say they learn new data-analysis and machine-learning skills. Plus, the best performers like the 95 “grandmasters” that top Kaggle’s rankings are highly sought talents in an occupation crucial to today’s data-centric economy. Glassdoor has declared data scientist the best job in America for the past two years, based on the thousands of vacancies, good salaries, and high job satisfaction. Companies large and small recruit from Kaggle’s fertile field of problem solvers. In March, Google came calling and acquired Kaggle itself. It has been integrated into the company’s cloud-computing division, and begun to emphasize features that let people and companies share and test data and code outside of competitions, too. Google hopes other companies will come to Kaggle for the people, code, and data they need for new projects involving machine learning—and run them in Google’s cloud..

As neuroscience brings greater understanding of the human brain, experts are applying those findings in the classroom to improve how we teach and learn.

In recent decades we’ve seen the rise of an emerging interdisciplinary field that brings together neuroscientists and educators. As technologies like brain mapping and scanning continue to advance our understanding of the human brain, a sub-sector of experts are applying those findings to the classroom. Instead of being based on traditional or individual assumptions about learning, education is beginning to be treated more like a science. The new discipline, neuroeducation, serves to apply the scientific method to curricula design and teaching strategies. This comes with attempts for a more objective understanding of learning that is based on evidence. What Is Neuroeducation? All human abilities, including learning, are a result of our brain activity. Hence, a better understanding of how our brains operate can result in a better understanding of learning. As we continue to unravel the issues and limitations of traditional education, many solutions involve a better scientific basis behind how we teach. The goal of neuroeducation (also known as mind and brain education or educational neuroscience) is to solidify a scientific basis in teaching and learning. The field uses the latest findings from neuroscience, psychology, and cognitive science to inform education and consequently, teaching strategies.

It shows findings in neuroeducation and how does that affect the nree metholodiges and techniques for teaching int he classroom, for instance that affective filters is linked with theories like neurolinguistic and linguistic programming, (you are able to understand and to perfom activities if you think you can do it and have the abilities to do it), another finding is that in the future mind mappings could be done per individuals of the brain, this means that teachers in the future will be able to understand the synapsis of the brain of the students, in order to know how they learn and how their neurons activate through different learning styles.

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